five

Lunar ASP DEM Test PDS4 Bundle

收藏
NIAID Data Ecosystem2026-03-14 收录
下载链接:
https://zenodo.org/record/7127152
下载链接
链接失效反馈
官方服务:
资源简介:
A pair of Ames Stereo Pipeline (ASP) generated LROC NAC Digital Elevation Models in NASA PDS4 structure. Purpose: Created as part of a testing effort funded by the LPI. The purpose of this dataset is to provide example LROC NAC Digital Elevation Models (DEMs) generated using rapid Ames Stereo Pipeline (ASP) processing. The example DEMs were assessed for suitability for scientific analysis. Data Set Overview: The archive contains 2 DEMs, in GeoTiff format, as a right image and a left image. The DEMs were generated using the ASP online tutorial and version of the software downloaded in March 2022 from github using the latest build (https://github.com/NeoGeographyToolkit/StereoPipeline). The DEMs cover a portion of Glushko crater's extensive ejecta ray system, Earth's Moon. The DEMs were generated using map-projected Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) input images that were collected as a stereo pair but have not yet been processed into a DEM using photogrammetric techniques. The base shape model for the projection is the LROC Wide Angle Camera (WAC) GLD100 topographic product. The map-projected images were run using parallel_stereo and point2dem processes in the ASP toolkit. The output is a DEM in geotiff format. The included test DEMs, archive structure, related documents, and xml files are formatted to best effort in pds4 format following online documentation by NASA PDS (as of Sept 2022 at https://pds.nasa.gov). Files were validated using the PDS Validate tool (downloaded Sept 2022, version v2.3.0, from https://github.com/NASA-PDS/validate). Xml templates were modified from existing related examples (Watkins 2018, Herrick and Ward 2020, Hare and Trent 2018). The provided files have been self-validated but are not validated by the Planetary Data System (PDS) and are provided for educational and training purposes only, and could contain errors or inconsistencies.
创建时间:
2022-09-30
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作